Many businesses and other enterprises are engaged in the transportation of objects from one location to another. Such transportation may occur on many different scales, e.g., ranging from transportation across a city to across the world, and from a few transportations per day to millions per day. The timing of such transportations is often a critical factor, yet it may be difficult to predict the timing with a desired degree of accuracy or reliability.
For example, many shipment companies and postal offices are engaged in the shipment of packages and other mailings. As just referenced, the timing of such shipments is often critical. For example, such companies may guarantee overnight (or some other timeframe, such as two-day or three-day) delivery of a package from an origin to a destination. If such companies are unable to meet these guarantees, then they may experience a loss of present and future revenue.
Conventional systems exist for collecting data regarding deliveries and other transportations of objects. For example, a company in charge of delivering a package may require that the package by tracked during its shipment, e.g., at each transportation leg and at each time the package is loaded, unloaded, sorted, or otherwise handled. Technology such as, e.g., bar code scanners and Radio Frequency Identifiers (RFID) may be used for such tracking. However, in a large delivery network, such tracking may quickly result in a huge database that becomes difficult to use in any practical way for ensuring that timing requirements will be met for future shipments.